The combined effects of FADS gene variation and dietary fats in obesity-related traits in a population from the far north of Sweden: the GLACIER Study

Abstract

BackgroundRecent analyses in Greenlandic Inuit identified six genetic polymorphisms (rs74771917, rs3168072, rs12577276, rs7115739, rs174602, and rs174570) in the fatty acid desaturase gene cluster (FADS1-FADS2-FADS3) that are associated with multiple metabolic and anthropometric traits. Our objectives were to systematically assess whether dietary polyunsaturated fat acid (PUFA) intake modifies the associations between genetic variants in the FADS gene cluster and cardiometabolic traits and to functionally annotate top ranking candidates to estimate their regulatory potential.MethodsData analyses consisted: interaction analyses between the six candidate genetic variants and dietary PUFA intake; gene-centric joint analyses to detect interaction signals in the FADS region; haplotype block-centric joint tests across 30 haplotype blocks in the FADS region to refine interaction signals; functional annotation of top loci. These analyses were undertaken in Swedish adults from the GLACIER Study (N=5,160); data on genetic variation and eight cardiometabolic traits was used.ResultsInteractions were observed between rs174570 and n-6 PUFA intake on fasting glucose (Pint=0.005) and between rs174602 and n-3 PUFA intake on total cholesterol (Pint=0.001). Gene-centric analyses demonstrated a statistically significant interaction effect for FADS and n-3 PUFA on triglycerides (P=0.005) considering genetic main effects as random. Haplotype analyses revealed three blocks (Pint<0.011) that could drive the interaction between FADS and n-3 PUFA on triglycerides; Functional annotation of these regions showed that each block harbours a number of highly functional regulatory variants; FADS2 rs5792235 demonstrated the highest functionality score.ConclusionsThe association between FADS variants and triglycerides may be modified by PUFA intake. The intronic FADS2 rs5792235 variant is a potential causal variant in the region having the highest regulatory potential. However, our results suggest that haplotypes may harbour multiple functional variants in a region, rather than a single variant.

Gene–Diet Interactions: Dietary Rescue of Metabolic Defects in spen-Depleted Drosophila melanogaster

“…Decades ago, the increased incidence of diabetes mellitus was attributed to an evolutionarily beneficial "thrifty" genotype that is incompatible with the modern Western diet and lifestyle (Neel 1962). Evidence of genetic adaptation to a diet high in polyunsaturated fatty acids can be found in the genomes of Greenlandic Inuit, in the form of genetic variants in fatty acid desaturases (Fumagalli et al 2015;Chen et al 2019). Accordingly, developing a comprehensive understanding of obesity and metabolic syndrome demands examination of the interplay between genetics and diet.…”

International Society for the Study of Fatty Acids and Lipids 2018 Symposium: Arachidonic and Docosahexaenoic Acids in Infant Development

“…FADS genotypes may account for up to 28% of the variability in serum fatty acid levels [63]. Polymorphisms in these genes may interact with dietary LCPUFA [64,65] affecting LCPUFA concentrations in breast milk, erythrocyte membranes, liver lipids, and other tissues. They have also been linked to the development of intelligence in children, coronary artery disease, acute myocardial infarction, allergic diseases, and other conditions [66] and could have implications for child health [67].…”

Nutrigenetics, omega-3 and plasma lipids/lipoproteins/apolipoproteins with evidence evaluation using the GRADE approach: a systematic review

“…In the observational studies assessing genetic variation in the FADS gene cluster, some studies indicated significant gene-diet findings related to HDL-cholesterol, LDL-cholesterol, TG, total-cholesterol while other studies demonstrated no significant gene-diet interactions for these outcomes thus indicating notable inconsistency among the results, while considering that SNPs differed by studies. 41 Vallée Marcotte et al 62 § § §Differences in population (healthy adults, adults with chronic disease or obesity, infants), some variation in length of follow-up. ¶ ¶ ¶Downgraded precision as it was not possible to assess precision in most studies due to lack of reporting of means and SD/SEM.…”